<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[hello__Jerry的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/hello__Jerry</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; hello__Jerry]]></copyright><item><title><![CDATA[python--join]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/105253998</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/105253998</guid><author>hello__Jerry</author><pubDate>Wed, 01 Apr 2020 19:55:57 +0800</pubDate><description><![CDATA[Python join()


str.join(seq)

方法用于将序列中的元素以指定的字符(str)连接生成一个新的字符串。


str = "-";
seq = ("a", "b", "c"); # 字符串序列
print (str.join( seq ));

输出：


a-b-c
...]]></description><category></category></item><item><title><![CDATA[数据可视化库Seaborn（3）热力图绘制]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/105210534</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/105210534</guid><author>hello__Jerry</author><pubDate>Mon, 30 Mar 2020 22:34:23 +0800</pubDate><description><![CDATA[%matplotlib inline
import numpy as np
import pandas as pd
import seaborn as sns
uniform_data = np.random.rand(3,3)
print(uniform_data)
heatmap = sns.heatmap(uniform_data)  #3x3矩阵热力图表现


 [[0.42899731...]]></description><category></category></item><item><title><![CDATA[数据可视化库Seabron（2）]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/105207904</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/105207904</guid><author>hello__Jerry</author><pubDate>Mon, 30 Mar 2020 22:19:17 +0800</pubDate><description><![CDATA[单变量分析绘图

直方图


import seaborn as sns
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy import stats,integrate
import pandas as pd
%matplotlib inline

sns.set(color...]]></description><category></category></item><item><title><![CDATA[python中group方法的使用]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/105163323</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/105163323</guid><author>hello__Jerry</author><pubDate>Sat, 28 Mar 2020 16:26:05 +0800</pubDate><description><![CDATA[正则表达式中，group（）用来提出分组截获的字符串，（）用来分组


import re
a = "123abc456"
print re.search("([0-9]*)([a-z]*)([0-9]*)",a).group(0)   #123abc456,返回整体
print re.search("([0-9]*)([a-z]*)([0-9]*)",a).group(1)   #123
pr...]]></description><category></category></item><item><title><![CDATA[数据可视化库-Seaborn]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/105082371</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/105082371</guid><author>hello__Jerry</author><pubDate>Wed, 25 Mar 2020 00:01:53 +0800</pubDate><description><![CDATA[import seaborn as sns
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
%matplotlib inline          #这句话的意思就是可以直接显示图


def sinplot(flip=1):
    x = np.linspace(0,14,100)    ...]]></description><category></category></item><item><title><![CDATA[数据可视化库--Matplotlib]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/105054137</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/105054137</guid><author>hello__Jerry</author><pubDate>Mon, 23 Mar 2020 21:41:46 +0800</pubDate><description><![CDATA[折线图


import pandas as pd
unrate = pd.read_csv('unrate.csv')
unrate['DATE'] = pd.to_datetime(unrate['DATE'])      #时间类型转换
print(unrate.head(12))



  DATE  VALUE
0  1948-01-01    3.4
1  1948-02-01    ...]]></description><category></category></item><item><title><![CDATA[数据分析处理库-pandas]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/105053583</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/105053583</guid><author>hello__Jerry</author><pubDate>Mon, 23 Mar 2020 17:51:51 +0800</pubDate><description><![CDATA[pandas提供了大量能使我们快速便捷地处理数据的函数和方法。

pandas中主要有两种数据类型：

Series:一维 带标签数组
	DataFrame:二维
DataFrame结构是由series构成的，series相当于矩阵当中的一行或者一列。

常用方法：


import pandas
food_info = pandas.read_cvs("food_info")
food...]]></description><category></category></item><item><title><![CDATA[科学计算库--numpy]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/105043974</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/105043974</guid><author>hello__Jerry</author><pubDate>Mon, 23 Mar 2020 16:21:00 +0800</pubDate><description><![CDATA[numpy（矩阵操作）

number = numpy.array([1,2,3,4]) -----其中参数都必须为相同的结构{关于array切片操作}

number.shape -------------查看矩阵的形状

number.dtype(A)-----------查看参数A的类型

number == 10 -------判断当前矩阵当中有没有值等于10

numpy.array操作...]]></description><category></category></item><item><title><![CDATA[python模块以及导入出现ImportError: No module named ‘xxx‘问题]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/79586034</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/79586034</guid><author>hello__Jerry</author><pubDate>Fri, 16 Mar 2018 19:39:51 +0800</pubDate><description><![CDATA[python中，每个py文件被称之为模块，每个具有__init__.py文件的目录被称为包。只要模块或者包所在的目录在sys.path中，就可以使用import 模块或import 包来使用如果你要使用的模块（py文件）和当前模块在同一目录，只要import相应的文件名就好，比如在a.py中使用b.py： import b 但是如果要import一个不同目录的文件(例如b.py)该怎么做呢？ 首先...]]></description><category></category></item><item><title><![CDATA[Django中的makemigrations]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/79585361</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/79585361</guid><author>hello__Jerry</author><pubDate>Fri, 16 Mar 2018 18:33:31 +0800</pubDate><description><![CDATA[当修改了model.py中的内容时，需要要执行第一步：python manger.py makemigrations 在该app下建立 migrations目录，并记录下你所有的关于modes.py的改动如：第二步：python manager.py migrate将该改动作用到数据库文件，比如产生table之类...]]></description><category></category></item><item><title><![CDATA[执行python manage.py makemigrations时报错：__init__() missing 1 required positional argument: 'on_delete']]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/79531532</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/79531532</guid><author>hello__Jerry</author><pubDate>Mon, 12 Mar 2018 19:34:29 +0800</pubDate><description><![CDATA[在执行python manage.py makemigrations时报错：TypeError: __init__() missing 1 required positional argument: 'on_delete'解决方法：            在连接外键时加上：on_delete=models.CASCADE...]]></description><category></category></item><item><title><![CDATA[初识Django]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/79404283</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/79404283</guid><author>hello__Jerry</author><pubDate>Wed, 28 Feb 2018 19:41:50 +0800</pubDate><description><![CDATA[WEB框架	MVC		Model       View       Controller		数据库   模板文件    业务处理			MTV		Model    Template     View                   （Django）		数据库   模板文件    业务处理安装Django ：pip3 install django	# 创建Django工程	django-admin...]]></description><category></category></item><item><title><![CDATA[初识数据结构与算法]]></title><link>https://blog.youkuaiyun.com/hello__Jerry/article/details/79404194</link><guid>https://blog.youkuaiyun.com/hello__Jerry/article/details/79404194</guid><author>hello__Jerry</author><pubDate>Wed, 28 Feb 2018 18:32:13 +0800</pubDate><description><![CDATA[数据结构：1.概念：数据结构：数据之间的关系，提高程序效率。逻辑关系：（人为认为）（1）、集合：在一个范围内有多个数据，数据之间没有关系。（2）、线性：1对1的关系（3）、树型：1对多的关系（4）、图：多对多的关系物理关系：内存存储1、顺序存储：数组（array）2、链式存储：链表（node相连）数据结构难不难：容易但是很难。数据结构有没有用：有用且没有用，锻炼自己的思维能力。ArrayList:...]]></description><category></category></item></channel></rss>